Accurate Control Research Articles

A Master-Slave-Structure Position Observer for Multiharmonics Suppression in Sensorless PMSM Drives

Due to the influence of inverter nonlinearity and nonideal spatial flux, it inevitably exists the back electromotive force (BEMF) harmonics in permanent magnet synchronous motor (PMSM) drives, affecting the accuracy of model-based position-sensorless control. Although different schemes have been studied to suppress the BEMF harmonics, it is still challenging to alleviate the contradiction between harmonics suppression effect and structure complexity. To address this problem, a master-slave-structure position observer is proposed for multi-harmonics suppression in this paper. With the help of the master-slave structure, the fundamental frequency component of the BEMF is extracted as the output of the studied observer, realizing the separation from the harmonic components. The number of the integrators can be reduced by half with the complex-coefficient resonators instead of the real-coefficient resonators. Thus, the design degree of freedom is fully exploited to realize the desired frequency-domain characteristics of band-pass and specific frequency band-stop. The studied method is verified by the experiments on a 2.2-kW PMSM platform.

LVRT Enhancement of DFIG-based WECS using SVPWM-based Inverter Control

Abstract: Across many countries, wind turbine generation systems (WTGS) have been established over the past few decades. In this paper, we augment the low voltage ride-through (LVRT) enrichment facility of driving a DFIG-based wind energy conversion system (WECS) using space vector pulse width modulation (SVPWM)-based inverter control. The proposed technique employs an SVPWM-based control algorithm to regulate the voltage and frequency of the output power during grid faults, thereby enhancing the WECS's ability to remain connected to the grid and provide power. The study focuses on decreasing transient current throughout the instant of fault. Modeling and control approaches were also discussed in this study. The performance of the proposed technique is evaluated using MATLAB/Simulink simulations, and the results demonstrate that the technique effectively improves the LVRT capability of the DFIG-based WECS. Background: Due to the variation in wind speed, the power generated by wind turbines is inconsistent. The power generated and the losses in wind turbines change correspondingly with changes in wind speed. The only type of machine that can generate power at speeds below the fixed speed is the doubly-fed induction generator (DFIG). But DFIG is oversensitive to network faults, which makes the bidirectional converters and DC link capacitor fail due to high inrush current and over-voltage. Methods: The converters connected to DFIG consist of an AC-to-DC converter, a boost converter, and a space vector pulse width modulation (SVPWM)-based DC-AC converter. The performance of the SVPWM controller is analyzed during symmetrical and unsymmetrical fault conditions. Results: The anticipated control provides adequate reactive power support to the network through the time of the fault and improves voltage and current waveform. The reactive power flow is also analyzed, and the effectiveness of the proposed controller is verified using MATLAB and Simulink. Conclusion: SVPWM (Space Vector Pulse Width Modulation)-based inverter control is an effective technique for wind energy conversion systems (WECS). The use of SVPWM can provide accurate and precise control of the AC voltage generated from the DC voltage source, resulting in improved system efficiency and reduced harmonic distortion in the output waveform. : The comparative analysis of THD suggests that SVPWM is a superior technique compared to other inverter control techniques such as sine-triangle pulse width modulation (SPWM) and carrier-based pulse width modulation (CPWM). SVPWM can help to reduce the distortion in the output waveform, leading to improved system efficiency, reduced wear on the system components, and overall better performance of the WECS. Furthermore, SVPWM offers several advantages over other inverter control techniques, including better utilization of DC voltage, improved voltage control, and better utilization of switching devices. These advantages make SVPWM a valuable tool for optimizing the operation of WECS and improving the reliability and performance of renewable energy systems. The value of THD for SVPWM inverter control in WECS is 1.53 under symmetrical fault and 1.34 for unsymmetrical fault, respectively. In summary, the use of SVPWM-based inverter control for WECS is an effective way to improve the efficiency and performance of the system while reducing the distortion in the output waveform and providing adequate reactive power support. The advantages of SVPWM over other inverter control techniques make it a valuable tool for the development and optimization of renewable energy systems.

Recursive dynamic modeling for attitude control of fully flexible spacecraft with central body and appendages

A spacecraft composed of a central body and flexible appendages is a typical rigid-flexible coupling system. Current modeling methods generally regard the central body as rigid. As the central body becomes larger and more flexible, the elastic deformation of the central body may not be ignored. In this study, considering the flexibility effect of the central body and based on the recursive kinematics, a complete coupled dynamic model of the orbit, attitude, and elastic deformation of a fully flexible spacecraft is established. Compared with traditional methods, the model has smaller generalized coordinate dimension and can more clearly reveal the kinematic relationship between the appendages and the central body. By comparing the simulation results of typical working conditions with the ADAMS software, the correctness of the built model is verified. The PD controller for the attitude of the spacecraft is used, and three models of different rigid/flexible settings are compared in detail. The dynamic response of the system in uncontrolled and controlled states are discussed. Numerical simulation results show that the flexibility of the central body poses a certain influence on the attitude response of the spacecraft, the flexible vibration of the appendages, and the attitude control accuracy.

A model-based sliding mode control with intelligent distribution for a proportional valve driven by digital valve arrays

Parallel-connected digital valve arrays are commonly utilized in the pilot stage of the proportional directional valve to enhance dynamic performance and reliability. However, when the digital valve array is driven by a digital signal, it is difficult to optimally assign the signal pulses to each valve. If the assignment is not well executed, it can significantly reduce the switching uniformity of the digital valves or lead to performance degradation of the system. In this paper, a model-based sliding mode control strategy based on the intelligent distribution of control law is proposed and successfully applied to a proportional valve driven by digital valve arrays. The intelligent distribution strategy encompasses a logic distribution algorithm and a circular sliding distribution algorithm that automatically assigns control laws to different valves based on the rolling of the PWM signal cycle. Experimental results confirm that the proposed strategy not only simultaneously reduces the total number of valve switches and enhances the switching uniformity among the valves, but also adapts to the variation in the number of valves. The proposed strategy is not limited to the application of digital valve arrays, it is also applicable in other fields of multi-actuators driven by digital signals, and can simultaneously improve the control accuracy, lifetime, and maintenance friendliness.

Rapid reconfiguration of gravitational detection spacecraft using high-accuracy successive convex programming

This article aims to address the challenge of achieving fast and high-accuracy reconfiguration of the TianQin constellation, with a focus on developing trajectory optimization algorithms to enhance both computation speed and accuracy in the reconfiguration process within TianQin Gravity Wave (GW) detection constellations. Initially, through perturbation analysis on the TianQin constellation, we formulated a dynamic model based on a virtual formation strategy, incorporating factors such as solar radiation pressure (SRP) and differences in third-body perturbation (DTBP). Subsequently, to meet the dual requirements of rapidly trajectory generation and optimal control accuracy, we proposed a new time-optimal high-accuracy successive convex programming (HASCP) algorithm and theoretically proved its convergence and optimality. Finally, we present simulations focusing on the TianQin gravitational detection spacecraft to validate the efficacy of the algorithm.

Fractional order adaptive sliding mode control method of manipulator

A new controller (NAFOFTSMC) is designed and successfully applied to the manipulator system. Compared with traditional integer-order sliding mode control methods (IOSMC), the fractional order sliding mode control method (FOSMC) adopted additional degrees of freedom and, to some extent, weakens the drawback of sliding mode control chattering problem. Fractional-order adaptive rate compensation is utilized to compensate for the total disturbance set of the system. The new sliding surface reduces the derivative signals that are difficult to obtain due to external interference and other factors in the robotic arm system. It also reduces the unknown parameters for adjustment, increases the proportion term, and thus enables the system to have higher control accuracy and shorter adjustment time. While designing the controller, the stability is proved at the end of the fourth section. At the same time, this control method was compared and analyzed with IOSMC, simple FOSMC, and a Pre-improved controller (AFOFTSMC).

A model-based control strategy for turbo-shaft engine

This paper takes the turbo-shaft engine (the power source of the helicopter) as the research object, and mainly conducts the simulation of its related control law and control structure. The working principle of the turbo-shaft engine is briefly introduced initially, and then the component-level model of the turbo-shaft engine is established. This paper focuses on the design of the control law upon the turbo-shaft engine, and verifies the designed control law through the results of simulation by MATLAB/Simulink. Finally, the relevant data collected from 240KW hybrid system is taken into the consideration to verify the control algorithm. The results show that the control accuracy of the corresponding control algorithm in this paper is high (accuracy≤5%).

Self-triggered formation attitude control for multiple spacecraft with disturbances

This paper studies the attitude consensus for nonlinear multi-spacecraft systems with disturbances and limited communication bandwidth and computing resources. A dynamic event-based attitude controller is developed to conserve communication resources, where a positive constant term is introduced to improve resource conservation efficiency. The developed event-driven controller is updated according to the constructed triggering mechanism, which greatly reduces the number of computations for the control algorithm. The triggering mechanism does not require continuous state information of neighboring spacecraft, which indicates that continuous communication is not needed for the operation of the formation system. Then, a self-triggered mechanism using the current triggering information is designed to further avoid continuous computation, and the avoidance of logarithmic functions enables the trigger interval to be close to that of the dynamic event-driven algorithm. The formation system is Zeno-free and uniformly ultimately bounded stable under the proposed event-based consensus control framework with the triggering strategies. Finally, simulations exhibit that the dynamic event-triggered protocol can reduce the communication frequency by 88%, and the self-triggered protocol can reduce the communication and computation frequency by 83% and have higher control accuracy than the dynamic event-triggered protocol.

Electro-Hydraulic Servo-Pumped Active Disturbance Rejection Control in Wind Turbines for Enhanced Safety and Accuracy

Aiming at the high accuracy and high robustness position control of servo pump control in the pitch system of a wind turbine generator, this paper proposes an active disturbance rejection controller (ADRC). The ADRC considers pitch angular velocity and acceleration limits. According to the kinematics principle of the pump-controlled pitch system, the relationship between the pitch angular velocity and acceleration limit and the displacement of the hydraulic cylinder is established. Through the method of theoretical analysis, the nonlinear relationship expression between pitch angle and hydraulic cylinder displacement is obtained, and the linearization of pitch angular velocity control is realized; the formula for b0 (the estimated value of the input gain of the system) of the pump-controlled pitch system is obtained by the method of modeling and analysis, b0 is the key parameter for the design of the ADRC; the stability of the controller parameters is proved through the stability analysis and simulation analysis, and the design of the self-immobilizing controller with pitch angular velocity and acceleration limitation is the completed ADRC design. Finally, a joint simulation platform of AMESim and MATLAB as well as a physical experiment platform of electro-hydraulic servo pump-controlled pitch control is constructed, and the effectiveness of the proposed control method is verified through simulation and experiment. The results show that compared with the unrestricted ADRC and PID, the velocity-acceleration-limited ADRC can effectively improve the control effect of the angular velocity and acceleration of the paddle, smooth the startup process, improve the safety of the system, and have better position control accuracy and anti-jamming ability.

Spacecraft relative on-off control via reinforcement learning

The article investigates the task of spacecraft relative control using reactive actuators, the output of which has two states, “on” or “off”. For cases where the resolution of the thrusters does not provide an accurate approximation of linear control laws using a pulse-width thrust modulator, the possibility of applying reinforcement learning methods for direct finding of control laws that map the state vector and the on-off thruster commands has been investigated. To implement such an approach, a model of controlled relative motion of two satellites in the form of a Markov decision process was obtained. The intelligent agent is presented in the form of “actor” and “critic” neural networks, and the architecture of these modules is defined. It is proposed to use a cost function with variable weights of control actions, which allows for optimizing the number of thruster firings explicitly. To improve the control performance, it is proposed to use an extended input vector for the “actor” and “critic” neural networks of the intelligent agent, which, in addition to the state vector, also includes information about the control action on the previous control step and the control step number. To reduce the training time, the agent was pre-trained on the data obtained using conventional control algorithms. Numerical results demonstrate that the reinforcement learning methodology allows the agent to outperform the results provided by the linear controller with the pulse-width modulator in terms of control accuracy, response time, and number of thruster firings.

Koopman operator-based multi-model for predictive control

AbstractThis work describes a new model structure developed for prediction in Model Predictive Control (MPC). The model has a multi-model structure in which independent sub-models are employed for the consecutive sampling instants. The model lifts process states into a high-dimensional space in which a linear process description is applied. Depending on the influence of the manipulated variables on lifted states, three general model versions are described and model identification algorithms are derived. As a result of the multi-model structure, model parameters are found analytically from computationally uncomplicated least squares problems using the Extended Dynamic Mode Decomposition algorithm, but the evolution of states over the horizon used in MPC is taken into account. Next, the MPC algorithm for the described model is derived. It requires solving online simple quadratic optimisation tasks. The effectiveness of three considered model configurations and three versions of the lifting functions is examined for a nonlinear DC motor benchmark. Their impact on model accuracy, complexity, possible control accuracy and MPC calculation time is thoroughly discussed. Finally, a more complex polymerisation reactor process is considered to showcase the practical applicability of the presented approach to modelling and MPC.

Research on the Influencing Factors of AUV Hovering Control in Null-Speed State

Intelligent underwater vehicles hover by way of a hovering control system. To provide design inputs and maneuver guidance, this study focused on the characteristics of intelligent underwater vehicles during hovering control with the propulsion system shut down, established a mathematical model of hovering control and determined injection and drainage functions based on optimal control theory. From analysis simulation experiments, the influence laws of control parameters, control timing and rate of injection and drainage control upon hovering control were deduced. It is proposed that, at the time of control parameter selection, the continuous injection and drainage rate at each time should be reduced as far as possible to relieve the demand on the volume of the reservoir when the requirement of depth control accuracy has been satisfied. In addition, the injection and drainage control should initiate when depth changes exceed 0.5 m. Suggestions are included on the minimum injection and drainage rate required for different initial disturbances. The proposed suggestions guide the design of hovering control systems and hovering control over intelligent underwater vehicles.

Integrated elastic identification and LOS angular rate extraction for slender rockets: A continuous-discrete maximum correntropy Kalman filter approach

Slender rockets experience significant elastic deformation during flight due to aeroelastic forces, impacting their dynamic behavior and posing challenges for traditional line-of-sight (LOS) angular rate estimation methods. This paper addresses this challenge by proposing a novel and highly accurate line-of-sight angular rate extraction model. This model integrates elastic identification with line-of-sight angular rate extraction, employing estimated generalized coordinates to calculate seeker elastic deformation. After elastic decoupling of the seeker, the slender rocket's line-of-sight angular rate can be estimated accurately. Additionally, the model incorporates a continuous-discrete maximum correntropy Kalman filter (CD-MCKF) to effectively handle the non-Gaussian measurement noise and limitations associated with discretizing the continuous model. Simulations demonstrate that the proposed method achieves significantly higher accuracy compared to existing approaches. The improved accuracy of this method can provide more precise calculations for the design of slender rocket guidance and control systems, ultimately improving the flight stability and control accuracy of rockets, and laying a solid foundation for the integrated guidance and control research of slender rockets.

Numerical Simulation of the Evaporation Behavior of Fe-Mn Heterogeneous Powder in Selective Laser Melting Process.

Multi-material additive manufacturing using heterogeneous powders as raw materials is one of the important development directions of metal additive manufacturing technology. The evaporation behavior of heterogeneous powders in the selective laser melting (SLM) process has a significant influence on the accuracy of chemical composition control and the quality of the final product. In this paper, the fusion process of Fe20Mn (80 wt.% Fe and 20 wt.% Mn) heterogeneous powder, Fe and Mn elemental powders, and Fe20Mn pre-alloyed powder is numerically simulated using FLOW-3D® software and partially validated through SLM experimental results. The morphology and the characteristics of the flow field and temperature field in the melt pool for four kinds of powder materials are analyzed. The influence of the elemental evaporation behavior of different powders on the mass loss of the Mn element is discussed. The results show that the excessive accumulation of heat increases the maximum temperature of the melt pool, thus increasing mass loss. The Fe20Mn heterogeneous powder has a wider heat-affected zone and a higher peak value of temperature, nearly 400 K higher than that of the Fe20Mn pre-alloyed powders, which exhibits an intensive evaporation behavior. The mass loss of the Mn element obtained from the SLM experiment for Fe20Mn heterogeneous powders forming parts is more than the Fe20Mn pre-alloyed powders' forming parts for different laser powers, up to 17 wt.% at P = 120 W. This tendency is consistent with the numerical analysis of the effect of evaporation behavior of Fe-Mn heterogeneous powder during the SLM process. This study provides the necessary theoretical reference and process guidance for realizing the precise control of the SLM composition of a heterogeneous powder in multi-material additive manufacturing caused by evaporation behavior.

Friction Coefficient of Wet Clutches as a Function of Service Mileage

As a core component for efficient variable speed transmission and energy saving, wet clutches are widely used in the transmission systems of energy-saving and new energy vehicles. However, with an increase in the service mileage of the wet clutch, the friction coefficient undergoes alterations. This leads to a deterioration of the control accuracy of the clutch transmission torque, which ultimately has a negative impact on the dynamic characteristics and driving safety of the entire vehicle. In order to understand the service behavior of the friction coefficient in a wet clutch, wet clutches with different service mileages were investigated experimentally and theoretically. The results show that as the service mileage increased, the hydrodynamic lubrication phase was extended. Analyses of the three-dimensional profile of the friction plate and the theoretical simulation of the friction revealed that the edge ridges of the friction pads were flattened. This increased the clutch engagement force when the asperities on the separator and friction plates came into contact.

A novel controllable bias reinforcement learning method for distributed automatic generation control integrated with large-scale electric vehicles

Due to the introduction of large-scale renewable energy resources and flexible load access, strong random disturbances will bring to the current integrated energy system. The traditional control methods fall short in adequately addressing the frequency regulation needs of distributed systems. From the perspective of distributed automatic generation control (AGC), an optimal coordinated control method is proposed based on reinforcement learning. The proposed method is developed to mitigate the estimation bias of the action-values via the minimum action-value from multiple action-value estimates. Further, the bias of action-value estimates can be adjusted from positive to negative to enhance the control accuracy. Then this method uses behaviour utility trace to achieve adaptive adjustment of the exploration rate, preventing repetitive and unbalanced exploration. Simulation experiments have been performed on the two-area LFC model integrated with electric vehicles and the multi-area integrated energy system model to verify the effectiveness of the proposed control method.

Reinforcement Learning May Demystify the Limited Human Motor Learning Efficacy Due to Visual-Proprioceptive Mismatch.

Vision and proprioception have fundamental sensory mismatches in delivering locational information, and such mismatches are critical factors limiting the efficacy of motor learning. However, it is still not clear how and to what extent this mismatch limits motor learning outcomes. To further the understanding of the effect of sensory mismatch on motor learning outcomes, a reinforcement learning algorithm and the simplified biomechanical elbow joint model were employed to mimic the motor learning process in a computational environment. By applying a reinforcement learning algorithm to the motor learning of elbow joint flexion task, simulation results successfully explained how visual-proprioceptive mismatch limits motor learning outcomes in terms of motor control accuracy and task completion speed. The larger the perceived angular offset between the two sensory modalities, the lower the motor control accuracy. Also, the more similar the peak reward amplitude of the two sensory modalities, the lower the motor control accuracy. In addition, simulation results suggest that insufficient exploration rate limits task completion speed, and excessive exploration rate limits motor control accuracy. Such a speed-accuracy trade-off shows that a moderate exploration rate could serve as another important factor in motor learning.

Research on Maximum Power Control of Direct-Drive Wave Power Generation Device Based on BP Neural Network PID Method

Ocean wave energy is a new type of clean energy. To improve the power generation and wave energy conversion efficiency of the direct-drive wave power generation system, by addressing the issue of large output errors and poor system stability commonly associated with the currently used PID (proportional, integral, and derivative) control methods, this paper proposes a maximum power control method based on BP (back propagation) neural network PID control. Combined with Kalman filtering, this method not only achieves maximum power tracking but also reduces output ripple and tracking error, thereby enhancing the system’s control quality. This study uses a permanent magnet linear generator as the power generation device, establishes a system dynamics model, and predicts the main frequency of irregular waves through the Fast Fourier Transform method. It designs a desired current tracking curve that meets the maximum power strategy. On this basis, a comparative analysis of the control accuracy and stability of three control methods is conducted. The simulation results show that the BP neural network PID control method improves power generation and exhibits better accuracy and stability.

Design and Development of Complex-Order PI-PD Controllers: Case Studies on Pressure and Flow Process Control

This article examines the performance of the proposed complex-order, conventional and fractional-order controllers for process automation and control in process plants. The controllers are compared regarding disturbance rejection and set-point tracking, considering variables such as response time, robustness to uncertainty, and steady-state error. The study shows that a complex PI-PD controller has better accuracy, faster response time, and better noise rejection. Still, implementation is challenging due to increased complexity and processing requirements. In contrast, a standard PI-PD controller is a known solution but may have problems with accuracy and robustness. Fractional-order controllers based on fractional computations have the potential to improve control accuracy and robustness of non-linear and time-varying systems. Experimental insights and real-world case studies are used to highlight the strengths and weaknesses of each controller. The findings provide valuable insights into the strengths and weaknesses of complex-order and fractional-order controllers and help to select the appropriate controller for specific process plant requirements. Future perspectives on controller design and performance optimization are detailed, identifying the potential benefits of using complex and fractional-order controllers in process plants.

Research on anti-vibration tension control based on self-coupling fractional-order PID

Constant tension control is essential for excellent winding quality. However, the system’s nonlinearity and external disturbance make it challenging to guarantee tension control accuracy with conventional control methods. Thus, a self-coupling fractional-order proportional–integral–derivative (SC-FOPID) control scheme combined with a disturbance observer is proposed to enhance the system’s anti-vibration performance. The fractional-order dynamic model of the unwinding roller and swing rod is established by analyzing the tension mechanism. Based on deliberate analysis and calculation, the vibration shock signal can be decomposed into periodic sinusoidal disturbance and bounded noise approximately. As such, an output-based anti-vibration method using a fractional-order model can be realized, where a back recursive disturbance observer is designed to estimate the periodic component. Simultaneously, the bounded noise exhibited in vibration can be attenuated by the SC-FOPID controller. The stability is guaranteed using the Lyapunov theorem, and the simulation results show the proposed method’s effectiveness in improving the tension control performance.